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Why Marketing Without Security Is A Serious Threat?

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Ad Fraud is not a term anymore that needs an introduction for marketers. There is frequent news about how fraudsters are evolving and stealing billions of dollars from marketers every year. As marketers are getting creative with their digital marketing efforts, fraudsters are also upgrading their fraud techniques. And as the fraudsters attempt to enter the new paid media realms like connected TV (CTV), the marketers have to become more vigilant. Meanwhile, the fraud security professionals have focused majorly on identity and payment fraud, the fraudsters have spread their horizons to trick the security professionals. They have evolved over time and came up with other forms of fraud methods like: Ecommerce Fraud Credential Stuffing Web Recon Malvertising Seeing the current threats from cybercriminals, it has become essential for marketers to collaborate with a holistic ad fraud detection and prevention solution. If you’re still not convinced, below we have covered the impact of ad fraud on vulnerable marketing and what is the solution. Impact of Ad Fraud on Vulnerable Marketing Lost Revenue: When the bots attack the marketing campaigns, an advertiser’s ad budget takes a toll. The advertisers are under the impression that their ad campaigns are attracting a load of traffic. However, the reality is that the traffic generated by bots is a waste. Even after investing a huge ad budget, the marketers neither get genuine traffic nor they are able to improve their ROI. Skewed Analytics: The success of an ad campaign is analyzed based on various metrics like site visits, clicks, and installs. However, when attacked by bots, these campaign data become skewed and give irrelevant data generated by bots from the campaign performance. This may further mislead the marketing teams into thinking their campaigns are performing well when in reality they are not. Poor Customer Experience: The brands attacked by the fraudsters do not just end up losing revenue, they have to deal with other problems related to the consumers. When the user clicks on a fraudulent ad, they have to incur problems like forced redirects or unauthorized malware installation. And, as a result, the consumer blames the brand for the inconvenience instead of considering it a fraudulent attack. Damage to Customer Trust: When a fraudster attacks a website or app, the consumer’s data is at risk. For instance, due to credential stuffing, the safety of the consumer’s account is compromised. The fraudsters hack their account to steal gift certificates and credit cards saved with the account. Furthermore, the brands lose time and money to invalid traffic while the genuine customers drift away upon feeling cheated. Holistic Way to Combat Ad Fraud Full-Funnel Model: For a marketing team, fraud detection must mean more than just eliminating fraud from ad campaigns. They must focus on other aspects like improved ROI and conversion rate along with cleaner traffic. To ensure this, the marketing team must focus on a full-funnel fraud detection model. This will help to eliminate the impact of sophisticated bots across the funnel. Real-Time Data Update: The marketing team must ensure to get real-time updates to take immediate action against ad fraud. With real-time ad fraud detection, marketers can optimize their ad campaigns before any serious loss. Due to real-time fraud detection, marketers can take an informed decision against fraudulent sources and protect their ad campaigns from the impact of fraud. Log-Level Data Analysis: To reduce false positives and take accurate measures against the sources of ad fraud, the marketers must have log-level data. By analyzing the log-level fraud data, the marketers can get an insight into the fraud sources, techniques, and how it is impacting their ad campaign. With the help of this detailed summary of fraud, marketers can take an informed decision for taking preventative actions. How mFilterIt can protect your marketing spends? To prevent wastage of ad spends on invalid traffic, our Ad Traffic Validation suite does deep checks to detect fraud at every stage of the sales funnel. Furthermore, our solution is equipped with features like real-time reporting and log-level fraud data. This helps the marketers to get a better understanding of how ad fraud has impacted their ad campaigns. Alongside this, we also ensure to do a transaction-level fraud analysis to detect fraudulent sources and blacklist them in real-time. Conclusion Ad fraud prevention is not a choice anymore for the marketing teams. No matter how much effort is given to optimize the ad campaigns, if the fraudsters manage to seep through the process, they can rip off all the ad spends. Thus, the marketing efforts must combine with a holistic ad fraud detection & prevention solution to ensure that the traffic coming on campaigns is – Clean Traffic AKA Real Humans. To ensure that your ad campaigns stay protected from ad fraud, get in touch with our ad fraud experts today!

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What’s the Deal with Brand Safety in Advertising?

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Brand safety is the process of protecting a brand’s image and reputation from the negative or damaging influence of questionable or inappropriate content when advertising online. It is important to have a deeper understanding of the subject to ensure the business’s success. For many companies, programmatic media has already become a part of their digital campaigns. In order to implement this strategy safely and efficiently, brand safety and brand suitability are two of the most commonly used branding concepts. By using these approaches, companies can stay protected in the digital environment and get the best results. Many organizations are currently at risk of disappearance if they do not invest in these concepts. Thus, it is necessary to understand what they mean and how they can be effectively used to guarantee the protection of a brand’s name in the online world. In this way, you will be able to avoid the main effects of unwanted online advertising. The purpose of this article is to explore the importance of brand safety in advertising and the steps to be taken to make it positive. Assured reputation In this context, the term safety refers to the reputation of the company and its safety. That is, to avoid being associated with crimes, adult content, fraud, hate speech, division, and fake news, among other controversial factors. Modern advertising is largely programmatic and brand safety is emerging in this context. Based on segmentation studies, the software decides where to advertise. It is necessary to have protection measures in place to ensure that these systems do not place the brand in inappropriate contexts. Associated with the concept is the idea of brand suitability, which is referring to what environments a company really belongs in. This means places where prospects go and are associated with a positive image that is valued by prospects. Since it is so easy to create ads and spread them across the internet, we can understand how brand safety is important as well. This is a hard-earned process that will directly contribute to the long-term success of your company. Your ads are an extension of your brand, and your users will judge you by what they see. What is the importance of brand safety in advertising? Even though advertising is mostly automated, you should protect your brand at all costs by ensuring positive interactions with your customers. The constant and extreme scrutiny social media offers are like a two-edged sword: mistakes in PR will make you vulnerable, but good advertising will also reach a wider audience. The risk can be mitigated by ensuring brand safety, understanding its strategies and tools, and establishing a detailed implementation plan to protect your reputation. What are some common issues that could threaten your brand’s safety? Here are a few brand safety problems that could harm your brand’s reputation. Take note of these while using programmatic advertising: Poor placement of ads The placement of your ad will have a significant impact on how people perceive it. If you place your ads on non-reputable websites or platforms, it can reflect badly on your business. Additionally, if ads appear next to provocative content, a negative association may be created between your brand and the content. Click-through rates and conversions can also be affected by the poor placement of ads. Customers are less likely to trust a company associated with shady sites or objectionable content. Fake news There is a lot of fake news circulating on the internet in the current political climate. It could damage your business’s reputation if your ad is displayed on a website spreading fake news. The users who see your ad next to fake news may think that your brand is associated with this information. Consequently, sales may suffer. Extremism Advertisements on websites or platforms that promote extremist views can damage your business’s reputation. Users may assume your company shares the same views if your ad appears next to extremist content. Additionally, placing ads on your site could lead them to believe you’re funding extremist content. Those people will distance themselves from your brand, which means you’ll lose prospects and actual customers. Ensuring your digital assets are safe at any point in time should be the brand’s responsibility. There are a few reasons for this: Ensures success in your digital marketing campaigns Implementing brand safety measures will make your digital marketing campaigns more successful. This is because your ads are more likely to appear in front of consumers who are interested or engaged in your product/service. Protecting your brand will prevent you from spending money on ads that will never be seen by your target audience. When your digital ad appears alongside offensive content, it will turn potential customers away from your brand. As more people avoid your ad, you’ll see a lower return on investment (ROI) for your digital marketing campaigns. It helps you reach the right audience According to a survey, about two-thirds (66%) of all companies, and 71% of companies with revenues greater than $10 billion, cite digital advertising as a primary value. Programmatic ads that are placed in a secure environment are more likely to engage your target audience. A user will be more likely to see your ad if they aren’t offended by the content surrounding it. Creates a positive first impression Your ad is often the first interaction your brand has with potential customers. It’s important to ensure that you’re making a good first impression. If your ad appears on a website promoting extremism or other vices, it will negatively reflect on your brand. Your ad will likely be remembered for all the wrong reasons and will make users less likely to do business with you in the future. Making a good first impression in business is key to attracting new customers and retaining them. Remember that potential clients will feel more comfortable doing business with you if your first impression is positive. Prioritize brand safety in advertising A digital advertising campaign is a great way to reach potential customers and promote your

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You Asked, We Answered: Most Searched Questions About Ad Fraud

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Whether you’re an advertiser, publisher, or user, it is natural to have questions about the growing threats of ad fraud. As the digital marketing world is moving ahead, the fraudsters are also becoming smart and coming up with new techniques to defraud marketers. Just like taking preventative measures against ad fraud is important, it is also essential to stay updated with the terms and techniques fraudsters are using. To ensure this, we have covered the most searched questions about ad fraud to help you understand the nitty-gritty of the techniques and tools used by fraudsters. Get ready to binge-read! What is ad fraud? Ad fraud is an attempt to defraud advertisers to steal money and manipulate their data with invalid traffic. The fraudsters usually use bots to perform ad fraud and trick the advertisers into thinking they are getting genuine users. As a result, the advertisers lose their ad revenue on invalid traffic. Furthermore, seeing the inflated traffic the advertisers think their ad campaigns are working and continue to invest in bot-impacted ad campaigns. According to a Juniper Research report, ad fraud is estimated to cost up to $81 billion by the end of 2022. What is bot traffic? Bot traffic consists of automated traffic coming from bots instead of humans. Every traffic generated from bots is not always fraudulent. Sometimes the search engines send bots to crawl the websites for ranking purposes. However, bot traffic is a concern when it is used as a carrier of ad fraud. Often called SIVT or sophisticated invalid traffic. The bad bots manipulate the data of an ad campaign and commit types of ad fraud like SDK spoofing, fake clicks, and fake installs. How to detect bot traffic? Some of the common ways to detect bot traffic that can be identified on websites, apps, and APIs are: Abnormally high pageviews Abnormally high bounce rate Inflated traffic from unknown locations Abnormal session durations High number of junk conversions What is Impression Ad Fraud? Impression means the total number of times an ad was displayed regardless of whether the ad was viewed or not. Impression fraud happens when the fraudsters create a fake website and list themselves on an ad exchange. When an advertiser buys an ad inventory on these websites, they generate impressions with the help of bots. The inflated impression numbers make the advertisers believe that their ad campaign is getting traffic. Wherein, the reality is that the ads are attracting bot traffic, and the fraudsters are getting money for invalid traffic. What is Ad Stacking? This is a type of mobile ad fraud where the fraudsters ‘layer’ or ‘stack’ multiple ads above one another in single ad placement. While just the top ad is visible to the user, the impression or click is registered for all the ads stacked beneath each other. This further lead to advertisers paying for a fake impression or click. What is VPN Proxy Click Fraud? A VPN is used to create a new IP address and mask the original location of a person. This is a strong tool for fraudsters to hide their tracks of ad fraud practices. With the help of a VPN proxy, they create a new IP address which helps them to keep themselves hidden from the ad fraud detection solutions. The fraudsters use this technique to mask their device location and commit fraud. What is Fake Attribution? A fake attribution is a practice followed by fraudsters to steal the credit of an organic install by reporting a fake click as the last engagement. Being the “last-click attribution”, the attribution platforms consider a fake click as an organic click. Usually, a fake attribution is triggered with a help of malware that comes along when a user installs an app from an unknown source. The malware helps to track the user’s activity and notifies the fraudster when the app install starts. The malware search for the relevant information and populates into a fake click report to register as the last click engagement and gets the attribution for an organic install or one generated by a media partner. What is cookie stuffing? This is a technique used in affiliate marketing fraud where a fraudulent affiliate fools the advertiser into thinking that they have sent traffic to their website. But in reality, they haven’t sent any traffic. This practice is also known as cookie dropping and is one of the commonly used techniques in affiliate marketing. By fooling the advertiser, they get the commission for sending a user to their website. Furthermore, the advertiser is wasting money and getting no users in return from their affiliate campaigns What is Ad Pixel stuffing? The technique of pixel stuffing happens when fraudsters place an ad or an entire website inside a frame of 1×1 pixel using an iframe. This makes it invisible to the human eye. When a normal ad runs, the impressions are tracked for the legitimate ad, as well as the ads that are stacked under the invisible pixel. In this way, the fraudsters receive compensation for those fake impressions. Furthermore, they also use bots to generate fake impressions with the pixel-stuffed ads and drain the advertiser’s budget on invalid traffic. What is Incent Fraud? This is a type of fraud where the fraudulent affiliates run non-incent campaigns on incent platforms. Due to this, they attract low-quality users that install only for incentives and have no interest in the actual app. This technique is usually used to increase the install volumes, fix low CR ratios, moderate the quality of user acquisition, or simply increase the margins. What is Click Injection? This is a sophisticated form of click-spamming which is majorly prevalent in android devices. When a user downloads a malicious app, they allow the fraudsters to detect when any other app is downloaded on a device. Once they know that, fraudsters trigger a click before an install is completed. As a result, the fraudster receives a credit for the install that appears legitimate and results in a CPI payout from the advertiser. What

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You’re Losing Genuine Users. Know Why?

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Imagine you’re running an ad campaign to generate leads for your clothing brand. You have also partnered with an ad fraud detection solution to detect and eliminate invalid traffic. However, one of your legitimate consumers raises a concern. Their card was blocked while making the transaction. Who could be responsible for this? You can blame the fraud detection vendor as they might have flagged a genuine consumer assuming it to be a fraudulent source. While ad fraud prevention is an essential element to eliminate fraudulent sources from ad campaigns, there must be a holistic way to differentiate between a genuine user and a bot without compromising the security of the ad campaigns. This mistake not only costs the brand their revenue, but also the trust of a legitimate user. Know how brands are impacted by this and what you must look for in an ad fraud detection vendor to avoid the case of false positives. What is a false positive? A false positive happens when a legitimate transaction is flagged as suspicious resulting in declining of payment or blocking of a genuine account. As a result, a request from a genuine customer is identified as a fraudulent source. This error happens when a non-fraudulent transaction is flagged by a fraud detection system resulting in the decline of the transaction. Why do false positives take place? The fraud detection systems are programmed to detect fraud patterns in a campaign. However, sometimes the system fails to accurately differentiate between a legitimate and a fraudulent request. As a result, the brand has to bear the collateral damage of false positives. To reduce the consequences of false positives, organizations have experimented with different approaches to try and differentiate between a legitimate and fraudulent user. Based on a checklist This list includes the details like IP addresses, email addresses, and Device IDs that have been identified and marked as either “safe” or “unsafe”. For example, if an IP address is flagged for being a source of malicious or fraudulent activity, then it will be “blacklisted”. Unfortunately, these lists are no longer viable to detect fast-evolving fraud. These lists require continuous refreshing as they get outdated in a short span of time. And these manually designed lists are often imprecise, corrupted, or at the worst expired. As a result, these reputation lists often lead to an increase in the number of false positives. Based on Rules The rules engines are software that is programmed to take actions based on specific criteria. For example, if a business has made a rule check to analyze the billing country and IP country. In this case, any mismatch will be an indication of a malicious account. These rules can be effective in some cases, but it has many limitations. The rules are highly reactive, and the results are based on past experiences. Furthermore, the rules are hard to manage especially in the case of large-scale data. As a result, the false positive number goes up. Based on Rule-based Machine Learning In this process, a training dataset is processed with the help of AI and ML. In this case, all the possible outcomes are programmed with the correct answers to train the algorithm. With the help of supervised machine learning, the brands can detect certain patterns and insights from a set of data. This is further used to make predictions about future outcomes. This is a strong tool for fraud detection, but it has its own limitations. For example, in SML the algorithms require a certain command to perform their tasks. This limits the ability to detect new and unknown fraud attacks. And as the fraudsters adapt to new techniques at a faster pace, it is impossible for an SML-based solution to keep pace. Why do brands need to act against false positives? Friction in users: Due to false positives, a genuine customer becomes the biggest victim. The most common case is when a customer attempts to pay to make a purchase, but for some unknown reason, the payment gets declined. A decline of a payment for an interested user can turn into a case of inconvenience and they drop out to purchase from a different brand or platform. Reputational damage: According to a report, 38% of online shoppers abandon their purchases when asked for an additional security check. They consider switching to a different brand when they experience poor service. Legitimate customers consider multiple layers of security and payment declines as an insult and often don’t take it in a positive light. Due to the inconvenience, sometimes they also end up spreading negative word-of-mouth which is a nightmare for the brands and tarnishes their brand reputation. Loss in revenue: Due to false-positive cases, not just the genuine consumers get impacted but also the brands. The brands lose the real customers and the potential revenue from genuine sales. In this case, the credit card companies have to bear the cost as they don’t get their fees. Questions to Ask your Ad Fraud Vendor to Reduce False Positives Do they analyze the entire lifecycle to ensure comprehensive protection? Do they look at all the possible types of fraud attacks? Do they identify and take preventive actions for new & emerging threats? Do they differentiate between legitimate and fraudulent activity in real-time? How mFilterIt ensure to reduce false positives? When detecting fraudulent sources in the ad campaigns, we expect an average of 4-5% false-positive cases. However, to ensure that the brand doesn’t have to lose genuine customers to protect its ad campaigns from fraudsters, our ad traffic validation suite ensures to focus on various parameters like: Deeper Fraud checks​ Evaluation for every data set to make a decision on​ Prioritization for sources that will convert ​ Able to detect sophisticated BOTS and emerging threats Analysis based on Behavioural and Deterministic data Conclusion A true ad fraud detection and prevention solution must be effective enough to help the brand in different parameters. A successful fraud detection will happen for a brand when it enhances the customer experience and nurtures them while keeping

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dcb-fraud

DCB Fraud: A Distress for All

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Direct Carrier Billing (DCB) is a subscription model offered by carrier providers. The charge of the availed subscriptions is added to the monthly mobile bill or deducted from the available balance, and generally transactions are made using a single click. According to a source, the DCB market is expected to grow by 9% between 2018 and 2022. Offering convenience through this model has substantially increased purchases & eliminates the need to fill in card details and account sign-ups. The user is already using the existing carrier number. The estimate number of smartphone users in India would reach 1132.9 million by 2025. India’s Average Revenue Per Paying User (ARPU) reached $3.9 by March 2021. Cybercriminals have been infiltrating mobile devices through general trojans, ransomware, password trojans, and others , with an average 93.93% of devices affected by general trojan malware. The Biggest Challenge of Operators Fraudsters use baits like malware/bots, Potentially Harmful Apps (PHAs), copycat apps, pirated content for downloading, etc., to acquire device access of unassuming device owners. Their two most crooked methods for DCB VAS frauds are iFrame and device farms. The bots/malware installed on the user device can even bypass USSD, CAPTCHA, and OTP & cause DCB fraud. DCB fraud means the carrier user is wrongly charged for subscriptions they have not made. Customers often disregard the charges, as they are minuscule, and rectifying them would take a toll of their time, with the added burden of talking with customer care, which often has long queues. End-user often becomes a victim of fraudulent charges. The mobile users who are victims of the unprovided/un-availed services blame the carrier providers for it. The operator must also answer to the telecom regulatory authority and face heavy fines or stop the services entirely. The lost faith in the carrier provider redirects revenue to competitors. Creates Complications for the Merchants Merchants suffer a loss of revenue if they become a victim of DCB fraud. They become as much liable as the MNOs, and in some instances, even more. Merchants often use marketing/advertising to increase their VAS subscribers. Unfortunately, fraudsters have found loopholes in their traffic generation methods. The actions of the cybercriminals lead to large-scale claims accumulated through defrauded customers, which evidently leads to fines, service cuts by the regulators & telcos, or suspensions. Regulators may adopt new methods for enhancing their payment security, which could diminish the VAS subscriptions, as consumers constantly face frictions and might even increase abandoned carts. Solution Against DCB Fraud mFilterIt’s DCB fraud solution offers a solution that helps brands across the globe to separate real users from bots/malware through our AI, ML, and data science. The solution validates the incoming traffic in real-time and safeguards brands at every step of the journey. It is an integrated fraud management solution for aggregators and operators. DCB fraud solution uses deterministic, heuristic, behavioral, and probabilistic parameters for classifying frauds. It eliminates frauds by risk scoring and real-time blocking. The live dashboard and real-time alerts optimize customer value management, enhance LTV, drive ROI, and diminish DCB fraud complaints. A Few Other Tips Don’t click on unnecessary URLs or visit suspicious pages/untrusted sources. Analyze the loss of partnership, revenue, and brand value caused by DCB fraud and take measures to overcome them by implementing mFilterIt’s anti-fraud solution for DCB. Take advice from our core founder and management team on the best practices or methods of implementing our solution and eliminating ad fraud. Conclusion The safety of the consumers also falls on the carrier provider in case of DCB frauds. Brands also lose trust, revenue, and customers if they cannot trust the carrier provider. The need to eliminate and restore the faith of the customer is now. This scenario is possible through DCB anti-fraud solution and implemented by global brands that want to keep their market reputation and sustain their market share. Moreover, the solution helps to detect and eliminate threats of real-time bot/malwares. Connect with us to learn more about the advantages of eliminating frauds in the DCB VAS ecosystem.

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What Aspects Does Sentiment Analysis of eCommerce Platforms Reveal?

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Customers on eCommerce platforms often check out reviews and ratings of products before making the final buying decision. In India, 48% of consumers make fashion purchases regularly after going through reviews and ratings. Monitoring reviews and ratings have become important for understanding customer sentiment towards the brand, product, seller, etc., across eCommerce platforms. Detecting and categorizing customer reviews as positive, neutral, and negative using mScanIt’s Sentiment Analysis enables to detect product aspect working ‘for & against’ the brand. mScanIt’s sentiment analysis dashboard defines sentiment intensity; segregates the most popular aspects like quality, product, price, etc., under comment themes; helps to find the most/least popular aspect/theme of a brand, etc. Diving deep into these aspects helps to keep track of consumer reviews across multiple eCommerce platforms, the most popular aspects/themes driving the sentiment intensity, pain points of the consumers, etc. mScanIt’s Sentiment Analysis also reveals key aspects of eCommerce platforms, which are useful for brands in multiple ways. A sentiment analysis is done by using What Can Brands Derive through mScanIt’s Sentiment Analysis? The Intensity of Buyer Reviews consumer reviews. Based on the consumer sentiments, a brand can understand the most popular aspect of its products on eCommerce platforms or can detect which aspects are meeting or not meeting to the buyer demands. A comparative view of the same vis-a-vis its competition enables a brand to learn the brand’s standing against its competition. For example, your brand could have a high (700+) positive reviews for ‘price,’ whereas your top competitor only has 200+ reviews on it. So, the consumers appreciate the price of the product and it is probably the leading factor driving your eCommerce sales/revenue under a category. On the other hand, your top competitor could have 500+ reviews on ‘quality’ whereas, you hardly reach 100 reviews on this aspect. Using this knowledge, you can evaluate your own Product Display Page (PDP) against your competition. It could show that the competitor is focusing more on ‘quality-based’ features and is using them in the advertising/marketing campaigns as well as the PDPs. P.S.: mScanIt can also be useful in analyzing PDPs, share-of-shelf, and banner ads. Probable Intent to Purchase According to research, the product purchasing decision of 91% of online shoppers rely on reviews from other customers. Therefore, listings on eCommerce platforms with higher positive reviews can increase add-to-cart actions and conversions. Furthermore, constantly checking sentiment analysis reveals the average sentiment score within a time frame. Therefore, brands can make sales forecasts and strategize accordingly. It’s one of the ways through which brands can understand the best performing ecommerce platform and optimize on their marketing spends. Moreover, the qualities/themes of the sentiment analysis dashboard would offer knowledge about the factors that might likely influence the customer’s intent to purchase. Points of Engagement with the Customers Reviewing mScanIt’s Sentiment Analysis dashboard gives information about the pain points of customers as well as the top-performing qualities of a product. It reveals the emotional triggers that can become responsible for trolling on eCommerce marketplaces under the review and rating section. Brands can use the emotional triggers generated from the ‘for and against’ reviews and ratings in their responses to improve the positive sentiment intensity and diminish the negative sentiment scores. The same information can be relayed to the marketing and customer support team to strategize and enable growth while addressing customer problems and enhancing the customer’s relationship with the brand. Reaching out to the customers at the right time by setting alerts of hyper sentiment intensities can help a brand to avoid trolls under the review and rating section as well as increase the brand’s ‘delightful’ customer base. Gain Insights About New Markets Customers on eCommerce platforms often reveal their pain points, compare the USPs of previously purchased products with recently purchased items, share the change in brand experiences, etc. Monitoring sentiment analysis reveals new buyer personas, untapped markets, trends, etc., which enable brands to build strategies for reaching out to the un-targeted customer base, increase their revenue, and plan marketing/advertising strategies for eCommerce platforms accordingly. Besides managing their sentiment analysis, brands get a chance to monitor competitors’ analysis tool using mScanIt, which expands all these horizons at a massive scale. Conclusion Monitoring sentiment analysis offers insights into customer behavior, such as the probable intent to purchase, points of engagement, responsiveness towards the product listing, etc. Keeping an eye on the sentiment analysis of eCommerce platforms can enable brands to customize their marketing and advertising strategies towards their buyer needs and even resolve problems whenever the negative sentiment intensity spikes up. Schedule a demo with us to learn methods to scale your business using mScanIt’s Sentiment Analysis.

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Your Search Ads Are Under Attack. Know Why?

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Akash is excited to plan his trip to Bali and starts searching for the best deals on the internet. He searches and finds an exciting deal of “Get INR 1000 instant cashback on your first hotel booking”. The deal sounded like a golden opportunity, and he instantly clicked on the ad. It was a renowned travel booking site which made him book his hotel in a hurry without any suspicion. However, he neither received the cashback nor the booking confirmation from the website even after 48 hours. In the end, he ends up being frustrated and is under the impression that he has been fooled by the brand. But in reality, the brand is clueless about this incident. In this case, Akash has been a victim of the search-ad phishing scam. This is one of the few instances which has recently been in the news in terms of cybercrime. Most of these instances often go overlooked due to a lack of awareness and prevention methods. The search ad scams not only result in the wastage of ad spends but also impact the reputation of the brand. Before knowing the impact, know in detail about search-ad phishing. What is Search-Ad Phishing? Also known as Google ad phishing, this is a type of cyberthreat in which the fraudsters hide the malicious links within the sponsored search engine results to fool people into clicking it. It is like phishing emails impersonating your brand just in the case of a search ad. When a person clicks on a search ad link, it redirects either to a fake website impersonating your brand, a spoofed social media account, or a fake phone number. Generally, the fraudsters trick the customers into searching for a website or customer care numbers of retail stores, financial institutions, insurance companies, cloud services, or utility companies. Ways Cybercriminals commit Search-ad Phishing Hacking Devices: The fraudster uses these techniques to trick users into sharing their personal information. Otherwise, they direct the users to an app or website to drop malware and hack their system to steal money or harvest personal information. Creating Fake Offers: The fraudsters also create fake company websites that claim to offer products at low prices for your brand’s products or services. When the customers fall for this bait, the fraudsters can use their personal information or sell counterfeit products using the name of the brand. Impact of Search-Ad Phishing on Brand Consumer Lose Trust: When the user interacts with a spoofed search ad, they are either taken to an impersonated website of a legitimate brand. The user is unaware of this and when they lose their money due to fraudulent practices, they think they have been defrauded by the brand. This eventually leads to consumers losing trust in the brand. Compromised Data: Due to the spoofed search ads, the data from the ad campaigns are highly compromised. This results in the wastage of ad spends and the advertiser unknowingly continues to invest in these tampered ad campaigns without any improvement in ROI. Conclusion Marketers often overlook the impact on brand safety when taking prevention measures from cybercriminals. Along with detecting fraud in ad campaigns, it is essential to act against brand infringement attacks by fraudsters. When the fraudsters attack your brand image, the consumers are impacted first and eventually lose trust in the brand. To protect your brand’s ad spends and brand safety altogether, it is important to partner with advanced ad protection and brand safety solution provider. mFilterIt’s ad traffic validation suite and brand safety suite ensure that your search ad campaigns are protected from invalid traffic and brand infringement attacks. With the right set of capabilities and expert help, protect your brand from the trap of fraudsters.

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How Is The Digital Advertising World Going to Look After the Collapse of Third-Party Cookies?

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The marketers have been feeding on third-party cookies data to reach a wide array of users based on their behavior and preferences. However, with the news of the third-party cookies phase-out, the marketers have to bring innovative ways to curate customer data for targeting the right audience with their ad campaigns. Google has announced that it will fade out the use of third-party cookies by the end of 2023 to bring more privacy to the digital ecosystem. But what will the next phase look like? Most certainly, it will not be that bad. Instead, it might be a start to a more transparent and privacy-first approach in the digital advertising world. Know in detail why third-party cookies are fading and how this will impact the advertisers and publishers. What are third-party cookies? The third-party cookies are used by marketers for ad retargeting and behavioral advertising. Advertisers add a tag to a page to track a user across the web as they visit different websites. This allows them to create a profile of a visitor based on their search habits so that they can show them more relevant ads. Advertisers have very sophisticated parameters for their campaigns to ensure they are reaching their targeted audience. To achieve this, they take the help of third-party cookies. However, third-party cookies have been under the radar of controversy for the longest time and are considered an invasion of people’s privacy. Why third-party cookies are going to phase out? The phase-out of third-party cookies has been in the buzz for quite some time. In February 2020, Google announced the phase-out to protect the privacy of the users. This move was initiated to bring more transparency, choice, and control to the users on how they want their data to be used. Though the search engine giant was the first to make the announcement, Safari and Firefox made the first steps to phase out third-party cookies. Google’s phasing out process will happen over a period of two years to ensure that the online advertising business is not impacted heavily by the change. Impact of Third-Party Cookies Phase-Out On Advertisers Out of all the cookies available on an average website, up to 60% are third-party that are used for marketing and advertising purposes. The third-party cookies are meant for tracking the behavior of the user across the internet. They capture the interests, actions, and behavior of the user as they scan through the websites. Though this data is quite broad and detailed with various data elements, the datasets made by combining cookie syncing and record matching give more comprehensive data for hyper-specific targeting. Due to the loss of this key mechanism, the advertisers will not be able to do retargeting, behavioral targeting, cross-site attribution modeling, and measurement. Without this kind of precision level, the reach and performance of the digital ads will also be impacted. On Publishers As the third-party cookies phase out, the publishers will not be able to provide a targeted audience to the advertisers. As a result, their ad revenue will be directly impacted. However, large publishers can use their first-party data to provide a highly targetable audience for the advertiser. Due to the phase-out of the third cookie, the ad exchanges, supply-side platforms (SSPs), or demand-side platforms (DSPs), addressability to the audience and volume will decline massively. Due to a weak targeted audience, the advertisers will pay a lost cost per impression as the ROAS will be low. How can marketers get ready for the change? The removal of third-party cookies will bring a drastic change in the digital advertising ecosystem. It will push the advertisers to create more authentic connections with customers. The first move after the phase-out will be to leverage the first-party cookie data. The use of first-party data means that the marketers will get access to more accurate and insightful data to measure customer interaction. Marketers have to brainstorm new ideas to build connections with their customers to get their contact details. However, the advertisers have to ensure that the customers trust them with their data. In addition to leveraging the first-party data, other techniques will help marketers to overcome the phasing out of third-party cookies. Some other ways are: Contextual advertising – To ensure that the right audience is targeted, the marketers will be required to focus on the messaging. A focused messaging will help provide a granular view of the interests of the audience. Federated Learning of Cohorts – This is a type of web tracking introduced by Google, but it is still in its testing phase. The basic idea of this technology is that the Chrome Browser will track the browsing habits of the customers and help the marketers to create a targeted messaging to attract the right audience. Will the first-party cookies result in low ad fraud? Unfortunately, No. Online marketers use cookies to gather user information for better ad targeting. While the third-party cookies compromised the privacy of the users sharing their information, their phasing out will not impact ad fraud. Even with first-party cookies, the fraudsters can generate invalid traffic with the help of bots, automated scripts, malware, and other non-human traffic. Though these fraudulent traffic sources can be identified with the help of IP addresses, there are some sophisticated fraud techniques like cookie stuffing which are hard to detect manually. How to protect your ad campaigns from ad fraud? To validate traffic on your web campaigns, it is essential to partner with an ad fraud detection & prevention solution like mFilterIt. We use sets of algorithms and capabilities of AI, ML, and data science to detect invalid traffic sources. Further, to protect your ad campaigns from future damage we do an active blacklisting to eliminate fraud and ensure cleaner traffic. Conclusion The fall of third-party cookies will bring a certain level of privacy and transparency to the digital advertising ecosystem. However, there will be hardly any impact on the ad fraud existing in the advertising world. Instead, the marketers will require strict preventative measures to protect their ad

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Why is DCB Fraud Problematic for Telcos?

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Carrier billing was considered to be one of the safest transaction mechanisms, but unfortunately that’s a myth. Mobile Network Operators (MNOs) provide internet and communication services to their customers directly as part of the telecom package. So, whenever fraud happens in the Direct Carrier Billing (DCB) ecosystem, it creates panic amongst the network’s consumers. Cybercriminals use sophisticated methods for targeting device users, such as malwares, bots, phishing emails/SMS, etc. Their undetectable and continuously evolving mechanisms directly impact the reliance on mobile subscriptions, which is increasing at a rapid pace. According to a source, there would be nearly 1.4 billion more mobile internet users by the end of 2025, and DCB service subscriptions would likely increase by three folds compared to 2019. As mobile internet users and DCB’s Value Added Service (VAS) subscriptions increases, fraudsters are bound to target customers, merchants, and network operators to acquire monetary benefits. Online transaction threats in the DCB subscription model have become problematic for telcos for many reasons. DCB Fraud Threatens Mobile Network Operators (MNOs) Loss of Consumer Trust and Market Credibility Customers making transactions through carrier billing have laid their trust in the MNOs. However, cybercriminals’ blatant disregard for consumer faith remains obvious during financial fraud. Moreover, the users blame the MNOs and merchants for losing their money for unrendered VAS subscriptions, recurring in their bills. While the rising customer complaints remain one flaw of the whole operation, the loss of revenue by paying back a sufficient amount to a larger group of users gives a financial blowback to the telco network. Therefore, it’s a constant battle for the brand custodians to make deliberate efforts to restore the faith of the users and ensure brand’s credibility. Besides fraud in the brand’s DCB transaction-based apps, the customers become victims of financial fraud on other associated apps. According to a research, users’ digital identities are sold for as small value as $25 on the dark web. Disables Telco from Achieving the Highest ARPU Average Revenue Per User (ARPU) is the estimated revenue generated by telcos/MNOs/brands based on active app users in a given period. It is calculated to understand the change in revenue generated per user, the change in total number of subscriptions in a specific duration, the sources that offer the maximum ARPU, etc. ARPU is also a term used in advertising for determining the campaigns generating the highest revenue, deciding the total number of user acquisitions for achieving revenue targets, deciding customer base, pricing strategy, etc. According to a report, the prepaid ARPU in Chile, Latin America, before the DCB service launch was $9 and post-launch was $19, which included an increase of $10 on core services and $9 on DCB. The same report also states that DCB also enhanced the subscription of core services (20%), prepaid recharge amounts (12%) & recharge frequencies (85%) for Telefonica prepaid subscribers. DCB fraud can create a loss of such potential revenue from brands. Moreover, victims of DCB fraud often switch to alternate MNOs that offer secure payments for subscriptions and don’t add unnecessary payments to the carrier bills. Besides, the customers could lose faith in DCB subscriptions and stop the DCB services completely. Drains the Digital Advertising Efforts MNOs across the globe often advertise their Value Added Services on search engines and other sources. In 2019, Google Ads attributed 54% of their ad sales to VAS mobile advertising, whereas affiliate networks generated the remaining advertising traffic. In the succeeding year, the share of Google Ads for VAS mobile advertising reached 62%,i.e., 8% higher. Whenever customers using DCB as payment for VAS subscriptions become victims of DCB fraud, their trust is lost in the MNOs. Moreover, customers often criticize the DCB service providers for the additional charge on their bills for unrendered services. Therefore, the likelihood that customers would click on ads associated with the MNO substantially diminishes, especially across social media handles, which, had a stake of 17% in 2020. What Can and Should MNOs Do to Eliminate the Threat of DCB Fraud? In these evolving times, MNOs need a technology-oriented solution and experts that have understanding about the modes of DCB fraud. Presently, mFilterIt’s DCB anti-fraud solution is a pioneer in the field of DCB. Our core team has more than a decade of experience in telecom network operations. Our solution eliminates the threat of DCB fraud by putting multiple levels of validation that allow brands to receive subscriptions from genuine users. In addition, the sophisticated solution categorizes the threat level and revokes DCB fraud by offering multiple mechanisms for device management. Conclusion The scale of DCB fraud increases every day with the increasing and evolving method of cybercriminal activities. Therefore, the current scenario requires mFilterIt’s DCB anti-fraud solution to validate legitimate subscriptions, avoid the drawbacks of DCB VAS fraud, increase ARPU, and safeguard advertising budgets aligned with VAS. As a MNO, it is also your responsibility to offer safe and secure environments for VAS subscriptions. Otherwise, you may also get penalized or have to stop the services altogether. Incorporating mFilterIt’s fraud prevention tool for DCB offers a resolution to such problems. Schedule a meeting with us to learn about the advantages of including our DCB anti-fraud solution in your consumer’s transaction journeys.

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How to Build a Robust Approach to Brand Safety?

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Programmatic native advertising is on the rise. It is a technique to incorporate marketing assets and messages into a publisher’s feed. Native ads that are purchased and placed programmatically provide brands with the opportunity to capitalize on increased relevance and personalization. Machine learning and contextual signals allow programmatic native ads to be tailored to the user, resulting in better performance for advertisers. A report shows that 1,900 advertisers invested $2.6 billion in the space between January and May 2021. Compared to 2020, when 926 advertisers spent $1.9 billion, it’s clear that advertisers want native advertising to be automated in order to maximize scale and efficiency. Yet, the growth of programmatic trading also poses a threat to brand safety, with some environments posing a risk of negative associations between buyers and sellers. In one recent instance, the Washington Post and New York Magazine inadvertently featured porn from an adult network whose video platform Vidme, which the publishers were using to embed other video content. The safety of brands is always a concern across the digital advertising industry, but it is particularly crucial for native ads. When ads are seamlessly integrated into their environments, it forms even stronger links between brands, publishers, and the content on the page. In order to maintain and enhance a close relationship with consumers, quality, relevance, and suitability are vital. In order to protect their reputations and identify optimal native placements, brands should consider the following steps. Choose your partners carefully Select ad networks that prioritize media security for programmatic and non-automated native ads, and monitor quality continuously. These trusted ad networks underpin private marketplaces (PMPs), which are where brands can find a reliable portfolio of premium publishers. PMPs establish a direct, transparent connection between the buy and sell sides, so advertisers can be assured that available media is vetted and meets their messaging and values. Brand safety requires careful selection of trading partners and native placements, but how can buyers ensure that they are not limiting their opportunities? To give advertisers granular control over what kind of content surrounds their ads, advertisers typically employ methods such as blacklists, whitelists, and keyword blocking. Despite being extremely valuable, especially when combined with other verification methods, these come with risks of their own. In order to avoid missing out on unexpected opportunities, advertisers need to be prepared to take action proactively. The rise in misinformation in 2020, for instance, led many brands to take a cautious approach to advertise around Covid-19 content. The pandemic was high on the news agenda, and therefore, brands minimized the size of their campaigns when not all content was safe. In fact, authoritative, optimistic, and educational content created positive associations for some brands. In order to take advantage of these opportunities, brands should adopt tools to identify native placements that are not only safe but also highly suitable. Artificial intelligence skills are used to power advanced contextual technologies capable of natural language processing (NLP) and semantic analysis. This technique extracts meaning from sentences and words based on grammatical structure, allowing one to categorize context and measure overall sentiment. Thus, contextual targeting ensures that environments and advertising content complement each other, enhancing brand messaging and engaging receptive audiences. Brands can then make more informed decisions based on the suitability of native placements to their brands. Make sure you ask the right questions Before planning how to mitigate risk, brands should speak with an agency or partner and ask three essential questions: What kind of protection does your solution provide for my brand? One-size-fits-all solutions do not account for the differences in values, objectives, and target audiences between brands. As a result, brands should find partners whose tools support customizable brand safety criteria. They can then select the media that is most appropriate and relevant to their products or industries. Are you able to prove that the technology works? To protect against risk, proven success is paramount when selecting the right partners and tools. Partners should demonstrate, for instance, how advanced brand safety technologies such as semantic analysis and natural language processing result in greater engagement rates. There is predicted growth in the NLP market from $3 billion in 2017 to more than $43 billion in 2025 – and where there is an investment, there is value. Therefore, you should ask the partners utilizing these technologies for results. What impact will your technology have on my reach? A brand’s safety is nuanced, and the technologies used to protect it must reflect this. By understanding linguistic complexities and reading content as the human brain does, brands will be able to take advantage of all possibilities to enhance their reputation through relevant and appropriate native placements. Reaching target audiences in a safe environment shouldn’t mean limiting reach. It is important for brands to make sure their digital advertising complements surrounding content and meets audience expectations. The success of native placements depends on how ads are integrated into the user experience. Conclusion An automated approach can enhance efficiency, but brands need a tailored strategy to determine brand suitability and build connections with ad-weary audiences. For native advertising to be effective, brands must partner with trusted ad networks, discuss brand safety criteria with their partners, and adopt technologies that identify brand-safe placements. By doing so, they will enhance their reputation by delivering relevant and engaging messages in a safe and optimal environment. By implementing mFilterIt’s Brand Hygiene Protection, brands can achieve higher relevance, revenue, and target audience. This solution helps to keep ads away from unsafe environments, fraudulent affiliates, and untrustworthy publishers.

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